Overview
Cipherlab ARS38PSTNNN12 RS38 Android Rugged Mobile Computer
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Bundle Summary
Overview
Cipherlab ARS38PSTNNN12 Rugged Mobile Computer with Rubber Boot
Overview
The Cipherlab ARS38PSTNNN12 is a rugged handheld mobile computer engineered for warehouse, logistics, and field operations. The integrated rubber boot provides added protection and grip for demanding environments. Built on Qualcomm QCM4490 Kryo Octa-core processing with 8GB LPDDR5 RAM and 128GB UFS3.1 storage, this device delivers reliable performance for inventory, scanning, and mobile workforce applications.
Key Specifications
IP65 rating ensures dust and water resistance for industrial use. Dual speaker audio at 85dB with three-microphone array and echo/noise reduction supports clear communication. Rear 16MP camera with PDAF and LED flash; front 8MP fixed-focus camera. Wi-Fi connectivity enables wireless integration into existing networks. Battery options include 4500mAh (268g) or 6800mAh (315g) configurations. Programmable keys and dedicated volume and trigger controls support customized workflows. microSD expansion up to 1TB accommodates large datasets and applications.
Compatibility
Designed for integration into Android-based mobile workforce management, logistics tracking, and asset inventory systems. Suitable for warehouse, retail, field service, and transportation environments requiring rugged, connected mobile computing.
System Design, Deployment & Technical Support
Support services and planning resources for commercial surveillance, access control, and infrastructure deployments.
Fixed scope • Fixed price
System Design Assistance
- Get help validating product compatibility
- Coverage requirements
- Storage planning and deployment architecture before you buy.
Deployment & Configuration Support
- Access fixed-scope support for rollout planning
- User setup guidance
- Migration and system standardization across single-site or multi-site deployments
Guides, Tools & Calculators
- PoE requirements
- Storage retention
- Camera selection and deployment methodology